Two of the big themes for wearable Health Tech these days are accuracy and lower power. Companies are raising the bar higher and higher on what is acceptable accuracy for wearable devices. And users want devices that last longer between charges, but at the same time they want smaller and lighter devices so simply adding bigger batteries is not the solution.
At CES 2017, I found a company that is taking a new approach to biometric sensors for wearable devices, and it could have a big impact on what we’ll be wearing in the coming years. Many devices — such as the Apple Watch — rely on optical sensors to measure things like heart beats. The problem is that many of these systems have problems with accuracy. For example, unless the device is in tight contact with the skin, light can leak into the gap and throw off the measurement. BioMindR is a Canadian company that has a different approach. Instead of using light, their sensor system relies on radio frequency (RF) waves. In addition to measuring heart rate, their system also tracks hydration, sodium levels, and blood sugar levels.
The system relies on complex machine learning to develop the algorithms that extract the useful data from the sensor signals. According to a company representative, the system has been shown to produce results equivalent to traditional blood draw clinical measures. The device currently uses separate transmission and receiver chips, but the next generation will combine both functions in a smaller package. One big advantage is that the sensor does not need to be in direct contact with the skin, which means it could be incorporated into smart garments. And compared with optical sensor systems, it requires about one-tenth as much power. This makes it practical to use for continuous monitoring, rather than just at certain intervals throughout the day.
